{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import scipy.io\n",
    "import csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = scipy.io.loadmat('./dataset/BITVehicle_Dataset/VehicleInfo.mat') # 读取mat文件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "VehicleInfo = data['VehicleInfo']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 1. 创建文件对象\n",
    "f = open('./dataset/label.csv','w',encoding='utf-8',newline='')\n",
    "\n",
    "# 2. 基于文件对象构建 csv写入对象\n",
    "csv_writer = csv.writer(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "num = 1\n",
    "for i in range(len(VehicleInfo)):\n",
    "    csvrecord = []\n",
    "    name = str(VehicleInfo[i][0][0][0])\n",
    "    clas = str(VehicleInfo[i][0][3][0][0][4][0])\n",
    "    class_num = class_name.index(clas)\n",
    "    csvrecord.append(str(num))\n",
    "    csvrecord.append(name)\n",
    "    csvrecord.append(class_num)\n",
    "#     print(csvrecord)\n",
    "    csv_writer.writerow(csvrecord)\n",
    "    num = num + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "f = csv.reader(open('./dataset/label.csv','r',encoding='utf-8'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "['9758', 'vehicle_0009758.jpg', '5']\n",
      "['9759', 'vehicle_0009759.jpg', '5']\n",
      "['9760', 'vehicle_0009760.jpg', '5']\n",
      "['9761', 'vehicle_0009761.jpg', '5']\n",
      "['9762', 'vehicle_0009762.jpg', '5']\n",
      "['9763', 'vehicle_0009763.jpg', '5']\n",
      "['9764', 'vehicle_0009764.jpg', '5']\n",
      "['9765', 'vehicle_0009765.jpg', '5']\n",
      "['9766', 'vehicle_0009766.jpg', '5']\n",
      "['9767', 'vehicle_0009767.jpg', '5']\n",
      "['9768', 'vehicle_0009768.jpg', '3']\n",
      "['9769', 'vehicle_0009769.jpg', '5']\n",
      "['9770', 'vehicle_0009770.jpg', '5']\n",
      "['9771', 'vehicle_0009771.jpg', '5']\n",
      "['9772', 'vehicle_0009772.jpg', '5']\n",
      "['9773', 'vehicle_0009773.jpg', '5']\n",
      "['9774', 'vehicle_0009774.jpg', '5']\n",
      "['9775', 'vehicle_0009775.jpg', '5']\n",
      "['9776', 'vehicle_0009776.jpg', '5']\n",
      "['9777', 'vehicle_0009777.jpg', '5']\n",
      "['9778', 'vehicle_0009778.jpg', '5']\n",
      "['9779', 'vehicle_0009779.jpg', '5']\n",
      "['9780', 'vehicle_0009780.jpg', '5']\n",
      "['9781', 'vehicle_0009781.jpg', '5']\n",
      "['9782', 'vehicle_0009782.jpg', '5']\n",
      "['9783', 'vehicle_0009783.jpg', '5']\n",
      "['9784', 'vehicle_0009784.jpg', '5']\n",
      "['9785', 'vehicle_0009785.jpg', '5']\n",
      "['9786', 'vehicle_0009786.jpg', '5']\n",
      "['9787', 'vehicle_0009787.jpg', '5']\n",
      "['9788', 'vehicle_0009788.jpg', '5']\n",
      "['9789', 'vehicle_0009789.jpg', '5']\n",
      "['9790', 'vehicle_0009790.jpg', '5']\n",
      "['9791', 'vehicle_0009791.jpg', '5']\n",
      "['9792', 'vehicle_0009792.jpg', '5']\n",
      "['9793', 'vehicle_0009793.jpg', '5']\n",
      "['9794', 'vehicle_0009794.jpg', '5']\n",
      "['9795', 'vehicle_0009795.jpg', '5']\n",
      "['9796', 'vehicle_0009796.jpg', '5']\n",
      "['9797', 'vehicle_0009797.jpg', '5']\n",
      "['9798', 'vehicle_0009798.jpg', '5']\n",
      "['9799', 'vehicle_0009799.jpg', '5']\n",
      "['9800', 'vehicle_0009800.jpg', '5']\n",
      "['9801', 'vehicle_0009801.jpg', '5']\n",
      "['9802', 'vehicle_0009802.jpg', '5']\n",
      "['9803', 'vehicle_0009803.jpg', '5']\n",
      "['9804', 'vehicle_0009804.jpg', '5']\n",
      "['9805', 'vehicle_0009805.jpg', '5']\n",
      "['9806', 'vehicle_0009806.jpg', '5']\n",
      "['9807', 'vehicle_0009807.jpg', '5']\n",
      "['9808', 'vehicle_0009808.jpg', '5']\n",
      "['9809', 'vehicle_0009809.jpg', '5']\n",
      "['9810', 'vehicle_0009810.jpg', '5']\n",
      "['9811', 'vehicle_0009811.jpg', '5']\n",
      "['9812', 'vehicle_0009812.jpg', '5']\n",
      "['9813', 'vehicle_0009813.jpg', '5']\n",
      "['9814', 'vehicle_0009814.jpg', '5']\n",
      "['9815', 'vehicle_0009815.jpg', '5']\n",
      "['9816', 'vehicle_0009816.jpg', '5']\n",
      "['9817', 'vehicle_0009817.jpg', '5']\n",
      "['9818', 'vehicle_0009818.jpg', '5']\n",
      "['9819', 'vehicle_0009819.jpg', '5']\n",
      "['9820', 'vehicle_0009820.jpg', '5']\n",
      "['9821', 'vehicle_0009821.jpg', '5']\n",
      "['9822', 'vehicle_0009822.jpg', '5']\n",
      "['9823', 'vehicle_0009823.jpg', '5']\n",
      "['9824', 'vehicle_0009824.jpg', '5']\n",
      "['9825', 'vehicle_0009825.jpg', '5']\n",
      "['9826', 'vehicle_0009826.jpg', '5']\n",
      "['9827', 'vehicle_0009827.jpg', '5']\n",
      "['9828', 'vehicle_0009828.jpg', '5']\n",
      "['9829', 'vehicle_0009829.jpg', '5']\n",
      "['9830', 'vehicle_0009830.jpg', '5']\n",
      "['9831', 'vehicle_0009831.jpg', '5']\n",
      "['9832', 'vehicle_0009832.jpg', '5']\n",
      "['9833', 'vehicle_0009833.jpg', '5']\n",
      "['9834', 'vehicle_0009834.jpg', '5']\n",
      "['9835', 'vehicle_0009835.jpg', '5']\n",
      "['9836', 'vehicle_0009836.jpg', '5']\n",
      "['9837', 'vehicle_0009837.jpg', '5']\n",
      "['9838', 'vehicle_0009838.jpg', '5']\n",
      "['9839', 'vehicle_0009839.jpg', '5']\n",
      "['9840', 'vehicle_0009840.jpg', '5']\n",
      "['9841', 'vehicle_0009841.jpg', '4']\n",
      "['9842', 'vehicle_0009842.jpg', '5']\n",
      "['9843', 'vehicle_0009843.jpg', '5']\n",
      "['9844', 'vehicle_0009844.jpg', '5']\n",
      "['9845', 'vehicle_0009845.jpg', '5']\n",
      "['9846', 'vehicle_0009846.jpg', '5']\n",
      "['9847', 'vehicle_0009847.jpg', '5']\n",
      "['9848', 'vehicle_0009848.jpg', '5']\n",
      "['9849', 'vehicle_0009849.jpg', '5']\n",
      "['9850', 'vehicle_0009850.jpg', '5']\n"
     ]
    }
   ],
   "source": [
    "for i in f:\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = 'vehicle_0000001.jpg'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'vehicle_0000001.jpg'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s[0:19]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "f = csv.reader(open('./dataset/label.csv', 'r', encoding='utf-8'))\n",
    "label_dict = {}\n",
    "for lists in f:\n",
    "    label_dict[lists[1]] = lists[2]\n",
    "#     label_dict.keys()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_dict[s]"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "grad",
   "language": "python",
   "name": "grad"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
